Guy Cavet
- Cancer Research top 1%
- Cancer Genomics and Diagnostics 5
- Molecular Biology top 1%
- RNA Interference and Gene Delivery 5
- Gene expression and cancer classification 5
- Advanced biosensing and bioanalysis techniques 4
- Genetics top 1%
- Oncology top 2%
- Aging top 5%
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- HIV Research and Treatment 4
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- Immune Cell Function and Interaction 4
- T-cell and B-cell Immunology 4
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- Monoclonal and Polyclonal Antibodies Research 3
- Co-authors
- Peter S. LinsleyJulja BurchardMao MaoSumire KobayashiSteven R. BartzAimee L. JacksonJanell M. SchelterBin Li
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Guy Cavet
32 papers receiving 7.0k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Cancer Research 1.3k
- Molecular Biology 5.6k
- Genetics 1.4k
- Oncology 1.2k
- Aging 67
Countries citing papers authored by Guy Cavet
This map shows the geographic impact of Guy Cavet's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Guy Cavet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guy Cavet more than expected).
Fields of papers citing papers by Guy Cavet
This network shows the impact of papers produced by Guy Cavet. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Guy Cavet. The network helps show where Guy Cavet may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Guy Cavet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2022 | 6 | |
| 3 | 2021 | 9 | |
| 4 | 2018 | 65 | |
| 5 | 2010 | 37 | |
| 6 | 2009 | 385 | |
| 7 | 2009 | 51 | |
| 8 | 2009 | 66 | |
| 9 | 2009 | 177 | |
| 10 | 2008 | 116 | |
| 11 | 2007 | 487 | |
| 12 | 2006 | 23 | |
| 13 | 2005 | 491 | |
| 14 | A large-scale RNAi screen in human cells identifies new components of the p53 pathwaybreakdown → | 2004 | 850 |
| 15 | 2004 | 374 | |
| 16 | Expression profiling reveals off-target gene regulation by RNAibreakdown → | 2003 | 1822 |
| 17 | Genetics of gene expression surveyed in maize, mouse and manbreakdown → | 2003 | 1105 |
| 18 | 2003 | 13 | |
| 19 | 2002 | 72 | |
| 20 | 1997 | 134 |
About Guy Cavet
Guy Cavet is a scholar working on Virology, Cancer Research, Immunology, Molecular Biology and Genetics, having authored 32 papers that have together received 7.3k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (5 papers), Cancer Genomics and Diagnostics (5 papers), Gene expression and cancer classification (5 papers), HIV Research and Treatment (4 papers), Immune Cell Function and Interaction (4 papers), Advanced biosensing and bioanalysis techniques (4 papers), T-cell and B-cell Immunology (4 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). The work is most often cited by research in Cancer Research (1.3k citations), Molecular Biology (5.6k citations), Genetics (1.4k citations), Oncology (1.2k citations) and Aging (67 citations). Guy Cavet has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Peter S. Linsley, Julja Burchard, Mao Mao, Sumire Kobayashi, Steven R. Bartz, Aimee L. Jackson, Janell M. Schelter, Bin Li, Lukas C. Amler and Eric E. Schadt. Their work appears in journals such as Clinical Cancer Research, Cancer Research, Cell, Molecular Cancer Research and Proceedings of the National Academy of Sciences.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.